Based on our record, Google App Engine should be more popular than DocParser. It has been mentiond 26 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
In 2008, Google launched AppEngine. This product predates the formal existence of Google Cloud and can be considered Google Cloud's first offering. - Source: dev.to / 1 day ago
To deploy the app, we can use Google Cloud App Engine, which is specifically built for server-side rendered websites. After we create a new project in the Google Cloud Console, we have to configure the cql-trace-viewer application. - Source: dev.to / 11 months ago
I've read that article, but I'm thinking there are other better (and most importantly cheaper) ways of doing that, such as using App Engine (given that you have to mitigate the maximum request timeout and to make sure there are constantly exactly 1 instance running). Source: 12 months ago
Shout out to GCP App Engine for deploying anode/Express severe. Source: 12 months ago
If your project is a bit more complicated using next.js or react.js or angular.js, you may find some free Platfrom-as-a-Service%20is%20a%20complete%20cloud%20environment,middleware%2C%20tools%2C%20and%20more.). I have seen some of my peers using free PaaS like Heroku, Vercel and I have no experience in using PaaS but I will recommend you to use PaaS from either of the three 1. Google Cloud's Google App Engine 2.... Source: about 1 year ago
You could try an online service like https://extract-io.web.app/ or https://docparser.com/. Source: 11 months ago
DocParser: DocParser simplifies the extraction of structured data from various file formats, such as PDFs and scanned documents, directly into Google Sheets. By automating this process, DocParser saves valuable time and effort otherwise spent on manual data entry. Link to DocParser. Source: 12 months ago
There are several tools available today that can help you extract tables from PDF files (such as Tabula), or even parse PDFs into structured JSON using AI (like Parsio -> I'm the founder) or without AI (like Docparser). Source: about 1 year ago
Thank you for sharing those! I didn't know them I've only checked this one https://docparser.com/ and I think my solution could be better because it will be easier for the user. Source: about 1 year ago
As previously suggested, if the layout of your PDFs never changes (consistent column widths in tables and placement), you can use a zonal PDF parser like DocParser. Alternatively, an AI-powered parser may be a better choice. Source: over 1 year ago
Salesforce Platform - Salesforce Platform is a comprehensive PaaS solution that paves the way for the developers to test, build, and mitigate the issues in the cloud application before the final deployment.
FlexiCapture - ABBYY FlexiCapture brings together the best NLP, machine learning, and advanced recognition capabilities into a single, enterprise-scale platform to handle every type of document. Available in the Cloud, on premise or as SDK.
Dokku - Docker powered mini-Heroku in around 100 lines of Bash
Amazon Textract - Easily extract text and data from virtually any document using Amazon Textract. Textract goes beyond simple optical character recognition (OCR) to also identify the contents of fields in forms and information stored in tables.
Heroku - Agile deployment platform for Ruby, Node.js, Clojure, Java, Python, and Scala. Setup takes only minutes and deploys are instant through git. Leave tedious server maintenance to Heroku and focus on your code.
Docsumo - Extract Data from Unstructured Documents - Easily. Efficiently. Accurately.